Lattice Boltzmann based discrete simulation for gas-solid fluidization

Discrete particle simulation, a combined approach of computational fluid dynamics and discrete methods such as DEM (Discrete Element Method), DSMC (Direct Simulation Monte Carlo), SPH (Smoothed Particle Hydrodynamics), PIC (Particle-In-Cell), etc., is becoming a practical tool for exploring lab-scale gas-solid systems owing to the fast development of parallel computation. However, gas-solid coupling and the corresponding fluid flow solver remain immature. In this work, we propose a modified lattice Boltzmann approach to consider the effect of both the local solid volume fraction and the local relative velocity between particles and fluid, which is different from the traditional volume-averaged Navier-Stokes equations. A time-driven hard sphere algorithm is combined to simulate the motion of individual particles, in which particles interact with each other via hard-sphere collisions, the collision detection and motion of particles are performed at constant time intervals. The EMMS (energy minimization multi-scale) drag is coupled with the lattice Boltzmann based discrete particle simulation to improve the accuracy. Two typical fluidization processes, namely, a single bubble injection at incipient fluidization and particle clustering in a fast fluidized bed riser, are simulated with this approach, with the results showing a good agreement with published correlations and experimental data. The capability of the approach to capture more detailed and intrinsic characteristics of particle-fluid systems is demonstrated. The method can also be used straightforward with other solid phase solvers.Comment: 15 pages, 11 figures, 2 tables. In Chemical Engineering Science, 201

COMPUTATIONAL FLUID DYNAMICS TECHNIQUES FOR MULTIPHASE FLOW SYSTEMS

Mathematical modelling of multiphase flow systems has been a major and persistent challenge over the last decades. Vast attempts to obtain predictive models can be found reported in literature, where major advances can be recognized in recent years, paired to enhancements in computer science and engineering. Notwithstanding, universally valid models with a mechanistic development are far from being achieved. The current status of modelling any multiphase flow system relies on the model order reduction of purely theoretical models. Such reductions and simplifications become the source of deviations in the predictions of the experimentally measured parameters and will constrain the applicability of the models. Hence, when modelling any multiphase flow system, there is a primal need of pairing mathematical modeling and experimental studies, in order to validate the models’ predictive quality, quantifying the deviations and providing a standpoint of the applicability and limitations of the models. In this sense, a successful multiphase flow system model should provide highly accurate local predictions, have a reduced number of possible sources of deviations (i.e., reducing the number of coupled sub-models, nor relying on vast simplifications), and have a high flexibility for being adapted or optimized to different conditions. In this work, it is sought to develop highly predictive, simplified and locally validated mathematical models by applying Computational Fluid Dynamics techniques, paired with other modelling and experimental techniques. Six cases of study are developed: i) Trickle Bed Reactors (TBR), ii) Packed Bed Reactors (PBR), iii) Fluidized Bed Reactors (FBR), iv) Spouted Bed Reactors (SBR), v) Heat transfer systems enhanced by nanofluids, vi) Bubble Column Reactors (BCR) --Abstract, p. i

Recent efforts on model-based simulation of engineering problems : multiphysics and multiphase interactions

Simulation-Based Engineering Science (SBES) is playing a more important role in gaining new knowledge and providing guidance for engineering activities, in particular, in the fields in which time scale and/or spatial scale make physical experiments dramatically expensive or even impossible. The success of SBES heavily relies on the development of algorithms that provide the bridge between the models describing physical and engineered systems and the computational devices that generate the digital representations of simulations. My efforts on the development of algorithms that simulate multiphysics and multiphase flow are presented in this dissertation. The first part of the dissertation describe the algorithms for the multiphysical model that simulates the laser drilling process. During laser drilling, heat conduction, melt flow, and vaporization occur in a very short time period. Vaporization also produces the recoil pressure that drives melt flow and complicates the heat transfer and material removal rate. To get a more realistic picture of the melt flow, a series of differential equations were developed that govern the process from pre-heating to melting and evaporation. In particular, the Navier-Stokes equation governing the melt flow is solved with the use of the boundary layer theory and integral methods. Heat conduction in a solid is investigated by using classic solutions with the corrections that reflect the change in boundary condition from constant heat flux to Stefan condition. The dependence of saturation temperature on the vapor pressure is taken into account by using the Clausius-Clapeyron equation. Both constantly rising radial velocity profiles and rising-fall velocity profiles are considered. In spite of the assumed varying velocity profiles, the new model predicts that the drilling hole profiles are very close to each other in a specific super alloy for given laser beam intensity and pulse duration. The numerical results show that the effect of melt flow on material removal can be ignored in some cases. The solutions derived can be applied to new cases to determine the role of melt flow and vaporization on laser drilling profile evolution and to study the solid material removal efficiency. The second part of this dissertation describes a new method that simulates the interaction between fluid and solid elements. The discrete element method (DEM) has been used to deal with the interactions between solid elements of various shapes and sizes, while the material point method (MPM) has been developed to handle the multi-phase (solid-liquid-gas) interactions involving failure evolution. A combined MPM-DEM procedure is proposed to take advantage of both methods so that the interaction between solid elements and fluid particles in a container could be better simulated. In the proposed procedure, large solid elements are discretized by the DEM, while the fluid motion is computed using the MPM. The contact forces between solid elements and rigid walls are calculated using the DEM. The interaction between solid elements and fluid particles are calculated via an interfacial scheme within the MPM framework. The proposed procedure is illustrated by representative examples. The convergence of numerical solutions and the factors affecting the simulation fidelity is also discussed

A three-phase interpenetrating continua approach for wave and porous structure interaction

This paper aims to propose a three-phase interpenetrating continua model for the numerical simulation of water waves and porous structure interaction

Hydrodynamic Behavior of Spouted Beds With Application to the Coating of Heart Valve Components.

Gas-solid fluidization is a subject having wide engineering applications overlapping different industries. A relatively unique application of fluidized bed technology resulted from a convergence of medical studies of thromboresistant materials with engineering development of gas impermeable and corrosion resistant coatings for artificial heart valves. The objective of this research was to study, through experimental measurements, gas-particle hydrodynamic behavior in the spouted bed, with an emphasis on biomedical manufacturing of prosthetic heart valves. Laboratory-scale and pilot-scale experiments were conducted to investigate the gas and solid phase behavior, such as minimum spouting velocity, pressure profile, particle velocity profile and particle density distribution. Gas phase hydrodynamics at different temperature were compared using two different physical models. Pressure fluctuation phenomena was also studied and related to the behavior of bed and gas-solid mixing. Experimental results were very promising. Pressure, particle velocity, and particle density distribution data will be further used to verify the numerical model. And they will also be used to direct the operation in the production unit of Sulzer Carbomedics Inc. Using a half-column model, stability of the spouted bed was analyzed both visually and using the pressure fluctuation analysis. Results showed that the reactor being used for pyrolitic coating of heart valve parts at Carbomedics Co., with the geometry of standard inlet and 40° of the cone angle, is operated at in the unstable regime. The geometry of the reactor plays an important role in determining the stability of the spouted bed. Experimental results also showed that the wall effect in the half-column model has negligible effect on the gas and solid phase behavior

Compaction and dilation rate dependence of stresses in gas-fluidized beds

A particle dynamics-based hybrid model, consisting of monodisperse spherical solid particles and volume-averaged gas hydrodynamics, is used to study traveling planar waves (one-dimensional traveling waves) of voids formed in gas-fluidized beds of narrow cross sectional areas. Through ensemble-averaging in a co-traveling frame, we compute solid phase continuum variables (local volume fraction, average velocity, stress tensor, and granular temperature) across the waves, and examine the relations among them. We probe the consistency between such computationally obtained relations and constitutive models in the kinetic theory for granular materials which are widely used in the two-fluid modeling approach to fluidized beds. We demonstrate that solid phase continuum variables exhibit appreciable ``path dependence'', which is not captured by the commonly used kinetic theory-based models. We show that this path dependence is associated with the large rates of dilation and compaction that occur in the wave. We also examine the relations among solid phase continuum variables in beds of cohesive particles, which yield the same path dependence. Our results both for beds of cohesive and non-cohesive particles suggest that path-dependent constitutive models need to be developed.Comment: accepted for publication in Physics of Fluids (Burnett-order effect analysis added

3D Modelling and Simulation of Reactive Fluidized Beds for Conversion of Biomass with Discrete Element Method

The use of biomass as a CO2–neutral renewable energy source gains more importance due to the decreasing resources of fossil fuels and their impact on the global warming. The thermochemical conversion of biomass in fluidized beds offers an economic and sustainable contribution to the global energy supply. Although the fluidized bed has reached a commercial status since many decades ago, its hydrodynamic behaviour is not completely understood. The availability of detail experimental information from real facilities is extremely difficult because the lack of accessibility, the measurement costs and the associated inevitable reduction in production. The numerical simulation provides an effective complement to the costly measurements. This requires besides the calculation of a gas-solid flow, an accurate description of particle–particle/wall collisions. Furthermore, kinetic models for pyrolysis, homogenous reactions, heterogeneous reactions and the related heat and mass transfer processes should be considered. Basically, there are two different methods for the representation of the gas–solid flow, viz. Euler–Euler and Euler–Lagrange models. The solid phase is treated as a continuum in the Euler–Euler model, while each particle trajectory is determined in the Euler–Lagrange model. In the Euler–Euler approach, the single particle-particle or particle-wall collision can be considered using additional assumptions. In the Euler–Lagrange approach, the particle-particle/wall collisions can be stochastically modeled or deterministically detected. The aim of this study is to develop a 3D program for the numerical simulation of biomass conversion in fluidized beds. The particle–particle/wall and gas–solid interactions are modeled by tracking all individual particles. For this purpose, the deterministic Euler–Lagrange/discrete element method (DEM) is applied and further developed. The fluid–particle interaction is studied using a new procedure, known as the offset method. The proposed method is highly precise in determining the interaction values, thus improving the simulation accuracy up to an order of magnitude. In this work, an additional grid, so-called particle grid, in which the physical values of solid phase is computed, is introduced. The suggested procedure allows the variation of the fluid grid resolution independent of the particle size and consequently improves the calculation accuracy. The collision detection between particle–particle/wall is performed with the aid of the particle search grid method. The use of the particle search grid method enhances the efficiency of collision detection between collision partners. The improved Euler–Lagrange/DEM model is validated towards the measurements obtained from a cold quasi–2D fluidized bed. The results suggest that the extended Euler–Lagrange/DEM model can predict accurately the motion of particles and the gas bubble expansion in the bed. The received results from the DEM model are also compared with other numerical approaches, namely the Euler-Euler and stochastic Euler–Lagrange models. Compared to measurements, the results show that the Euler–Euler model underestimates the bubble sizes and the bed expansions, while the stochastic Euler–Lagrange model reaches faster the maximum bed expansions. The efficiency and accuracy of the Euler–Lagrange/DEM model is investigated in detail. Parameter studies are carried out, in which stiffness coefficient, fluid time step and processor number are varied for different particle numbers and diameters. The obtained results are compared with the measurements in order to derive the optimum parameters for Euler–Lagrange/DEM simulations. The results suggest that the application of higher stiffness coefficients (more than 10^5 N/m) improves the simulation accuracy slightly, however, the average computing time increases exponentially. For time intervals larger than five milliseconds, the results show that the average computation time is independent of applied fluid time step, while the simulation accuracy decreases extremely by increasing the size of fluid time step. The use of fluid time steps smaller than five milliseconds leads to negligible improvements in the simulation accuracy, but to exponential rise in the average computing time. The parallel calculation accelerates the Euler–Lagrange/DEM simulation if the critical number of domain decomposition is not reached. Exceeding this number, the performance is not anymore proportional to the number of processors and the computational time increases again. The critical number of domain decomposition depends on particle numbers. An increase in solid contents results in a shift of critical decomposition number to higher numbers of CPUs. The local concentrations of solid and gaseous species, the local gas and particle temperatures, the local heat release and heat transfer rates can also be calculated with the developed program. In combination with the simulation of the gas–solid flow, it is possible to model the biomass conversion in the fluidized bed. Three series of warm simulations in a quasi–2D fluidized bed model are performed, viz. combustion with fuel gas without and with inert sand particles as well as combustion with solid fuel (a mixture of inert sand and pine wood particles). The received results realise the coupling of the Euler–Lagrange/DEM model with chemical reaction mechanism. The extended Euler–Lagrange/DEM model under the consideration of thermochemical reaction model is able to simulate, by the same token, the conversion of other solid fuels such as coal in fluidized beds

Development of 6-way CFD-DEM-FEM momentum coupling interface using partitioned coupling approach

peer reviewedFluid-particle-structure interactions (FPSI) govern a wide range of natural and engineering phenomena, from landslides to erosion in abrasive water jet cutting nozzles. Despite the importance of studying FPSI, existing numerical frameworks often simplify or neglect certain physics, limiting their applicability. This work introduces a novel 6-way CFD-DEM-FEM momentum coupling for FPSI using a partitioned coupling approach, providing a flexible and adaptable solution. Our prototype uses the preCICE coupling library to couple three numerical solvers: OpenFOAM for fluid dynamics, eXtended Discrete Element Method (XDEM) for particle motion, and CalculiX for structural mechanics. The coupling approach extends existing adapters and introduces a novel XDEM preCICE adapter, allowing data exchange over surface and volumetric meshes. Numerical experiments successfully demonstrate the 6-way coupling, showcasing fluid-structure interactions and particle dynamics. The versatility of the partitioned coupling approach is highlighted, allowing the interchangeability of different single-physics solvers and facilitating the study of complex FPSI phenomena. This article offers a thorough description of the methodology, coupling strategies, and detailed results, offering insights into the advantages and disadvantages of the proposed approach. This work lays the groundwork for a scalable and customizable FPSI simulation framework with a wide range of applications